Download of the image databases generated during the challenge: the 4 teams participating in the challenge and the operational consortium are proud to share with you all the image databases generated during the challenge. Fill in the form to access the download.

LNE-MATICS software suite : free and open-source software suite designed for data mining and system evaluation. It was originally designed for the evaluation of Automatic Language Processing systems, and will eventually be used to evaluate a wider range of artificial intelligence systems. LNE also provides a training session on the software suite.

Revue Ouverte d’Intelligence Artificielle, Volume 2 (2021) no. 1, pp. 11-32.
Novembre 17th, 2021
Validation of methodologies for evaluating autonomous weed control solutions, in the framework of the Challenge ROSE and METRICS projects.

Workshop EPAI – EVALUATING PROGRESS IN AI
1st International Workshop held in conjunction with ECAI 2020 – September 4th, 2020
Design and validation of testing facilities for weeding robots as part of ROSE Challenge

FIRA – Workshop ROBAGRI – December 2019 – Detection task evaluation

3RDF Colloquium, Thursday, December 5, 2019 (Colloquium proceedings)

Research-industry day september,26 2019 :

• Program
• Introductory présentations
• Présentations – Highlight 1
• Présentations – Highlight 4

3rd RDV technique AXEMA : Boosting agricultural scientific research and innovation through challenges: the ROSE Challenge example

CIAG Numerique in plant production: predicting and acting – June 2018

By PEAD:

Autonomous Vision-Based Navigation and Control for Intra-Row Weeding – Avilès, J., Soto, D., Stéphant, J., Labbani-I., O., 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (proceedings très prochainement)

A proposal was submitted to IEEE ICRA 2023 (international conference on Robotics and Automation) https://www.icra2023.org/ : YoCo v1: Real-time Crop Instance Segmentation –  Jesus Franco-Robles, Jorge E. Avilès-Mejia and Ouiddad Labbani-Igbida

By BIPBIP:

Lac L., Keresztes B., Louargant M., Donias M., Da Costa J.-P. (2022). An annotated image dataset of vegetable crops at an early stage of growth for proximal sensing applications. Data in Brief, Volume 42, 108035. https://doi.org/10.1016/j.dib.2022.108035

Lac L., Da Costa J.-P., Donias M., Keresztes B., Bardet A. (2022). Crop stem detection and tracking for precision hoeing using deep learning. Computers and Electronics in Agriculture, Volume 192, 106606, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2021.106606.

Louargant M., Lac L., Da Costa J.-P., Donias M., Keresztes B., Gimbert H., N’Guyen, Labriffe E., Bondu L., Kaçar F. (2022). BIPBIP: a mechanical and automated intra-row weeding solution. Accepted at the Int. Symposium on Mechanization, Precision Horticulture and Robotics: Precision and Digital Horticulture in Field Environment. International Horticultural Congress, Angers, France, August 2022.

Lac L., Da Costa J.-P., Donias M., Keresztes B., Louargant M. (2021). SDNet: Unconstrained Object Structure Detector Network for In-Field Real-Time Crop Part Location And Phenotyping. British Machine Vision Conference, United Kingdom. Online presentation.

Lac L., Gréteau G., Keresztes B., Rançon F., Bardet A., Da Costa J.P. (2019). Embedded vision system and algorithms for early weed vs. crop discrimination within the row. Proceedings of ECPA 2019, Montpellier, France.

Others actions by BIPBIP

By WeedElec :

Julien Champ, Adan Mora‐Fallas, Hervé Goëau, Erick Mata‐Montero, Pierre Bonnet, Alexis Joly. (2020) Applications in plant sciences (Vol 8 – Issue 7): Instance segmentation for the fine detection of crop and weed plants by precision agricultural robots

Champ, Julien; Mora-Fallas, Adan; Goëau, Hervé; Mata-Montero, Erick; Bonnet, Pierre; Joly, Alexis. (2020) An annotated visual dataset for Automatic weed detection and identification – doi 10.5281/zenodo.3906501 

By ROSEAU :

Hassan NEHME – Sitia/Irseem CIFRE thesis:  “Perception of the navigation environment for an autonomous robot in an agricultural environment” Defended in June 2022

• Nehme, Hassan, Clément Aubry, Thomas Solatges, Xavier Savatier, Romain Rossi, and Rémi Boutteau. “LiDAR-based Structure Tracking for Agricultural Robots: Application to Autonomous Navigation in Vineyards.” Journal of Intelligent & Robotic Systems 103, no. 4 (2021): 1-16
• Nehme, Hassan, Clément Aubry, Romain Rossi, and Rémi Boutteau. “An Anomaly Detection Approach to Monitor the Structured-Based Navigation in Agricultural Robotics.” In 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), pp. 1111-1117. IEEE, 2021
• Nehme Hassan “Détection de nouveauté et d’anomalie pour le suivi de structure autonome” during the webinar “IA et robotique agricole” of RobAgri association. 2020

Jehan-Antoine VAYSSADE – UMR Agroécologie Dijon thesis: “Multi-criteria approach for the characterization of weeds by imagery” Defended in March 2022

• Vayssade, Jehan-Antoine, Gawain Jones, Christelle Gée, and Jean-Noël Paoli. “Pixelwise instance segmentation of leaves in dense foliage.” Computers and Electronics in Agriculture 195 (2022): 106797
• Vayssade, Jehan-Antoine, Jean-Noël Paoli, Christelle Gée, and Gawain Jones. “DeepIndices: Remote Sensing Indices Based on Approximation of Functions through Deep-Learning, Application to Uncalibrated Vegetation Images.” Remote Sensing 13, no. 12 (2021): 2261
• Vayssade, Jehan-Antoine, Gawain Jones, Jean-Noël Paoli, and Christelle Gée. “Two-step Multi-spectral Registration Via Key-point Detector and Gradient Similarity: Application to Agronomic Scenes for Proxy-sensing.” In VISIGRAPP (4: VISAPP), pp. 103-110. 2020
• Vayssade, Jehan-Antoine, Jean-Noël Paoli, Christelle Gée, and Gawain Jones. “DeepIndices: Une nouvelle approche des indices de télédétection basée sur l’optimisation et l’approximation de fonctions par DeepLearning. Application aux indices de végétation sur des données non calibrées.” In Conference: RJCIA: Rencontres des Jeunes Chercheur· ses en Intelligence Artificielle. 2021

The ROSE Challenge chosen as an example of application for robotic evaluation in the Deep Learning and Agriculture study of the AgroTIC Chair : download the study

See the first photo/video montage of the field meetings

See the video presenting the last evaluation campaign of the challenge

Description of the ROSE Challenge – December 2019 (french version)

Flyer challenge-rose – March 2018 (french version)

On the occasion of the 29th edition of the Fête de la Science organised from 2nd to 12th October 2020 – Daily Live Science broadcast animated by the Sorcerer Spirit in the sequence “The fertile future of soils”. Click here to see the replay of the show. (The replay on the ROSE challenge starts at about 1h25).

On France 3 ARA, Tuesday 9th October 2019 – 5 minutes subject. Click here to see the replay of the programme.

In Actu’DGER – Le mensuel de la Direction Générale de l’Enseignement et de la Recherche – nr 3 from november, 2020 : click here.